Hi-AI

analyze_requirements

Read-onlyIdempotent

Analyze project requirements to identify essential features, prioritize needs, and define constraints using structured methods like MoSCoW or Kano analysis.

Instructions

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "requirements": "<requirements>"
    },
    "name": "analyze_requirements"
  }
}

Input Schema

Name	Required	Description	Default
`requirements`	Yes	List of requirements to analyze
`stakeholders`	No	Project stakeholders (e.g., users, admins, developers)
`constraints`	No	Project constraints (timeline, budget, technical)
`analysisMethod`	No	Analysis method	moscow

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 15, 2025

TDQS

C2.9/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, which already convey that this is a safe, non-destructive, and deterministic operation. The description adds no behavioral context beyond this, such as rate limits or authentication needs. However, it does not contradict the annotations, so it meets the lower bar set by the annotations without adding significant value.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a repetitive list of phrases ('요구사항 분석|필요한 것들|requirements analysis|what we need|analyze requirements|필수 기능 - Analyze project requirements') that lack structure and front-loading. It wastes space by restating the same concept in multiple languages without adding clarity or value, making it inefficient and poorly organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (4 parameters, 100% schema coverage, annotations provided, no output schema), the description is incomplete. It fails to explain what the analysis outputs or how it integrates with sibling tools, leaving gaps in understanding the tool's role. However, annotations cover safety and determinism, partially compensating for the description's shortcomings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with clear descriptions for all parameters (e.g., 'requirements' as a list to analyze, 'analysisMethod' with enum options). The description adds no parameter semantics beyond what the schema provides, such as explaining how parameters interact or their impact on analysis. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description '요구사항 분석|필요한 것들|requirements analysis|what we need|analyze requirements|필수 기능 - Analyze project requirements' is vague and repetitive. It lists multiple phrases that essentially restate the tool name ('analyze requirements') without specifying what the analysis produces or how it differs from sibling tools like 'analyze_complexity' or 'analyze_problem'. The purpose is implied but lacks specificity about the verb+resource outcome.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, nor does it differentiate from sibling tools such as 'analyze_complexity' or 'generate_prd'. Without such information, the agent must infer usage from the tool name alone, which is insufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.